Multiple antenna channel tracking under practical impairment

ABSTRACT

Methods and apparatuses for a BS in a communication system. The method comprises: identifying antenna groups; identifying channel coefficients for each of the antenna groups to perform a channel tracking and prediction operation; receiving, from a user equipment (UE), an uplink signal to perform the channel tracking and prediction operation; and performing, based at least in part on the received uplink signal, a channel coefficient tracking operation for the channel coefficients of the antenna groups, respectively, the channel coefficient tracking operation including a channel subspace parameter tracking operation and a subspace coefficient tracking operation.

CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM OF PRIORITY

The present application claims priority to U.S. Provisional PatentApplication No. 63/152,133, filed on Feb. 22, 2021. The content of theabove-identified patent document is incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates generally to wireless communicationsystems and, more specifically, the present disclosure relates to amultiple antenna channel tracking operation under practical impairmentcondition.

BACKGROUND

5th generation (5G) or new radio (NR) mobile communications is recentlygathering increased momentum with all the worldwide technical activitieson the various candidate technologies from industry and academia. Thecandidate enablers for the 5G/NR mobile communications include massiveantenna technologies, from legacy cellular frequency bands up to highfrequencies, to provide beamforming gain and support increased capacity,new waveform (e.g., a new radio access technology (RAT)) to flexiblyaccommodate various services/applications with different requirements,new multiple access schemes to support massive connections, and so on.

SUMMARY

The present disclosure relates to wireless communication systems and,more specifically, the present disclosure relates to a multiple antennachannel tracking operation under practical impairment condition.

In one embodiment, a base station (BS) is provided. The BS comprises aprocessor configured to: identify antenna groups and identify channelcoefficients for each of the antenna groups to perform a channeltracking and prediction operation. The BS further comprises atransceiver operably connected to the processor, the transceiverconfigured to receive, from a user equipment (UE), an uplink signal toperform the channel tracking and prediction operation, wherein theprocessor is further configured to perform, based at least in part onthe received uplink signal, a channel coefficient tracking operation forthe channel coefficients of the antenna groups, respectively, thechannel coefficient tracking operation including a channel subspaceparameter tracking operation and a subspace coefficient trackingoperation.

In another embodiment, a method of a BS is provided. The methodcomprises: identifying antenna groups; identifying channel coefficientsfor each of the antenna groups to perform a channel tracking andprediction operation; receiving, from a user equipment (UE), an uplinksignal to perform the channel tracking and prediction operation; andperforming, based at least in part on the received uplink signal, achannel coefficient tracking operation for the channel coefficients ofthe antenna groups, respectively, the channel coefficient trackingoperation including a channel subspace parameter tracking operation anda subspace coefficient tracking operation.

In yet another embodiment, a non-transitory computer-readable medium isprovided. The non-transitory computer-readable medium comprising programcode, that when executed by a processor, causes a base station (BS) to:identify antenna groups; identify channel coefficients for each of theantenna groups to perform a channel tracking and prediction operation;receive, from a user equipment (UE), an uplink signal to perform thechannel tracking and prediction operation; and perform, based at leastin part on the received uplink signal, a channel coefficient trackingoperation for the channel coefficients of the antenna groups,respectively, the channel coefficient tracking operation including achannel subspace parameter tracking operation and a sub spacecoefficient tracking operation.

Other technical features may be readily apparent to one skilled in theart from the following figures, descriptions, and claims.

Before undertaking the DETAILED DESCRIPTION below, it may beadvantageous to set forth definitions of certain words and phrases usedthroughout this patent document. The term “couple” and its derivativesrefer to any direct or indirect communication between two or moreelements, whether or not those elements are in physical contact with oneanother. The terms “transmit,” “receive,” and “communicate,” as well asderivatives thereof, encompass both direct and indirect communication.The terms “include” and “comprise,” as well as derivatives thereof, meaninclusion without limitation. The term “or” is inclusive, meaningand/or. The phrase “associated with,” as well as derivatives thereof,means to include, be included within, interconnect with, contain, becontained within, connect to or with, couple to or with, be communicablewith, cooperate with, interleave, juxtapose, be proximate to, be boundto or with, have, have a property of, have a relationship to or with, orthe like. The term “controller” means any device, system, or partthereof that controls at least one operation. Such a controller may beimplemented in hardware or a combination of hardware and software and/orfirmware. The functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely. Thephrase “at least one of,” when used with a list of items, means thatdifferent combinations of one or more of the listed items may be used,and only one item in the list may be needed. For example, “at least oneof: A, B, and C” includes any of the following combinations: A, B, C, Aand B, A and C, B and C, and A and B and C.

Moreover, various functions described below can be implemented orsupported by one or more computer programs, each of which is formed fromcomputer readable program code and embodied in a computer readablemedium. The terms “application” and “program” refer to one or morecomputer programs, software components, sets of instructions,procedures, functions, objects, classes, instances, related data, or aportion thereof adapted for implementation in a suitable computerreadable program code. The phrase “computer readable program code”includes any type of computer code, including source code, object code,and executable code. The phrase “computer readable medium” includes anytype of medium capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, acompact disc (CD), a digital video disc (DVD), or any other type ofmemory. A “non-transitory” computer readable medium excludes wired,wireless, optical, or other communication links that transporttransitory electrical or other signals. A non-transitory computerreadable medium includes media where data can be permanently stored andmedia where data can be stored and later overwritten, such as arewritable optical disc or an erasable memory device.

Definitions for other certain words and phrases are provided throughoutthis patent document. Those of ordinary skill in the art shouldunderstand that in many if not most instances, such definitions apply toprior as well as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure;

FIG. 2 illustrates an example gNB according to embodiments of thepresent disclosure;

FIG. 3 illustrates an example UE according to embodiments of the presentdisclosure;

FIGS. 4 and 5 illustrate example wireless transmit and receive pathsaccording to this disclosure;

FIG. 6 illustrates an example antenna structure according to embodimentsof the present disclosure;

FIG. 7 illustrates a flowchart of a method for a channel predictionoperation according to embodiments of the present disclosure;

FIG. 8A illustrates an example tracking and prediction operationaccording to embodiments of the present disclosure;

FIG. 8B illustrates an example antenna array for tracking and predictionoperation according to embodiments of the present disclosure;

FIG. 9 illustrates an example ToFo impact removal operation beforeentire processing according to embodiments of the present disclosure;

FIG. 10 illustrates an example ToFo impact removal operation after thesubspace tracking operation according to embodiments of the presentdisclosure;

FIG. 11 illustrates an example antenna differentiation operationfollowed by channel tracking operation according to embodiments of thepresent disclosure; and

FIG. 12 illustrates a flowchart of a method for a multiple antennachannel tracking procedure according to embodiments of the presentdisclosure.

DETAILED DESCRIPTION

FIGS. 1 through FIG. 12, discussed below, and the various embodimentsused to describe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged system or device.

FIGS. 1-3 below describe various embodiments implemented in wirelesscommunications systems and with the use of orthogonal frequency divisionmultiplexing (OFDM) or orthogonal frequency division multiple access(OFDMA) communication techniques. The descriptions of FIGS. 1-3 are notmeant to imply physical or architectural limitations to the manner inwhich different embodiments may be implemented. Different embodiments ofthe present disclosure may be implemented in any suitably-arrangedcommunications system.

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure. The embodiment of the wireless network shownin FIG. 1 is for illustration only. Other embodiments of the wirelessnetwork 100 could be used without departing from the scope of thisdisclosure.

As shown in FIG. 1, the wireless network includes a gNB 101 (e.g., basestation, BS), a gNB 102, and a gNB 103. The gNB 101 communicates withthe gNB 102 and the gNB 103. The gNB 101 also communicates with at leastone network 130, such as the Internet, a proprietary Internet Protocol(IP) network, or other data network.

The gNB 102 provides wireless broadband access to the network 130 for afirst plurality of UEs within a coverage area 120 of the gNB 102. Thefirst plurality of UEs includes a UE 111, which may be located in asmall business; a UE 112, which may be located in an enterprise (E); aUE 113, which may be located in a WiFi hotspot (HS); a UE 114, which maybe located in a first residence (R); a UE 115, which may be located in asecond residence (R); and a UE 116, which may be a mobile device (M),such as a cell phone, a wireless laptop, a wireless PDA, or the like.The gNB 103 provides wireless broadband access to the network 130 for asecond plurality of UEs within a coverage area 125 of the gNB 103. Thesecond plurality of UEs includes the UE 115 and the UE 116. In someembodiments, one or more of the gNBs 101-103 may communicate with eachother and with the UEs 111-116 using 5G/NR, long term evolution (LTE),long term evolution-advanced (LTE-A), WiMAX, WiFi, or other wirelesscommunication techniques.

Depending on the network type, the term “base station” or “BS” can referto any component (or collection of components) configured to providewireless access to a network, such as transmit point (TP),transmit-receive point (TRP), an enhanced base station (eNodeB or eNB),a 5G/NR base station (gNB), a macrocell, a femtocell, a WiFi accesspoint (AP), or other wirelessly enabled devices. Base stations mayprovide wireless access in accordance with one or more wirelesscommunication protocols, e.g., 5G/NR 3GPP NR, long term evolution (LTE),LTE advanced (LTE-A), high speed packet access (HSPA), Wi-Fi802.11a/b/g/n/ac, etc. For the sake of convenience, the terms “BS” and“TRP” are used interchangeably in this patent document to refer tonetwork infrastructure components that provide wireless access to remoteterminals. Also, depending on the network type, the term “userequipment” or “UE” can refer to any component such as “mobile station,”“subscriber station,” “remote terminal,” “wireless terminal,” “receivepoint,” or “user device.” For the sake of convenience, the terms “userequipment” and “UE” are used in this patent document to refer to remotewireless equipment that wirelessly accesses a BS, whether the UE is amobile device (such as a mobile telephone or smartphone) or is normallyconsidered a stationary device (such as a desktop computer or vendingmachine).

Dotted lines show the approximate extents of the coverage areas 120 and125, which are shown as approximately circular for the purposes ofillustration and explanation only. It should be clearly understood thatthe coverage areas associated with gNBs, such as the coverage areas 120and 125, may have other shapes, including irregular shapes, dependingupon the configuration of the gNBs and variations in the radioenvironment associated with natural and man-made obstructions.

As described in more detail below, one or more of the UEs 111-116include circuitry, programing, or a combination thereof, for a multipleantenna channel tracking operation. In certain embodiments, and one ormore of the gNBs 101-103 includes circuitry, programing, or acombination thereof, for a multiple antenna channel tracking operation.

Although FIG. 1 illustrates one example of a wireless network, variouschanges may be made to FIG. 1. For example, the wireless network couldinclude any number of gNBs and any number of UEs in any suitablearrangement. Also, the gNB 101 could communicate directly with anynumber of UEs and provide those UEs with wireless broadband access tothe network 130. Similarly, each gNB 102-103 could communicate directlywith the network 130 and provide UEs with direct wireless broadbandaccess to the network 130. Further, the gNBs 101, 102, and/or 103 couldprovide access to other or additional external networks, such asexternal telephone networks or other types of data networks.

FIG. 2 illustrates an example gNB 102 according to embodiments of thepresent disclosure. The embodiment of the gNB 102 illustrated in FIG. 2is for illustration only, and the gNBs 101 and 103 of FIG. 1 could havethe same or similar configuration. However, gNBs come in a wide varietyof configurations, and FIG. 2 does not limit the scope of thisdisclosure to any particular implementation of a gNB.

As shown in FIG. 2, the gNB 102 includes multiple antennas 205 a-205 n,multiple RF transceivers 210 a-210 n, transmit (TX) processing circuitry215, and receive (RX) processing circuitry 220. The gNB 102 alsoincludes a controller/processor 225, a memory 230, and a backhaul ornetwork interface 235.

The RF transceivers 210 a-210 n receive, from the antennas 205 a-205 n,incoming RF signals, such as signals transmitted by UEs in the network100. The RF transceivers 210 a-210 n down-convert the incoming RFsignals to generate IF or baseband signals. The IF or baseband signalsare sent to the RX processing circuitry 220, which generates processedbaseband signals by filtering, decoding, and/or digitizing the basebandor IF signals. The RX processing circuitry 220 transmits the processedbaseband signals to the controller/processor 225 for further processing.

The TX processing circuitry 215 receives analog or digital data (such asvoice data, web data, e-mail, or interactive video game data) from thecontroller/processor 225. The TX processing circuitry 215 encodes,multiplexes, and/or digitizes the outgoing baseband data to generateprocessed baseband or IF signals. The RF transceivers 210 a-210 nreceive the outgoing processed baseband or IF signals from the TXprocessing circuitry 215 and up-converts the baseband or IF signals toRF signals that are transmitted via the antennas 205 a-205 n.

The controller/processor 225 can include one or more processors or otherprocessing devices that control the overall operation of the gNB 102.For example, the controller/processor 225 could control the reception ofUL channel signals and the transmission of DL channel signals by the RFtransceivers 210 a-210 n, the RX processing circuitry 220, and the TXprocessing circuitry 215 in accordance with well-known principles. Thecontroller/processor 225 could support additional functions as well,such as more advanced wireless communication functions. For instance,the controller/processor 225 could support beam forming or directionalrouting operations in which outgoing/incoming signals from/to multipleantennas 205 a-205 n are weighted differently to effectively steer theoutgoing signals in a desired direction. Any of a wide variety of otherfunctions could be supported in the gNB 102 by the controller/processor225.

The controller/processor 225 is also capable of executing programs andother processes resident in the memory 230, such as an OS. Thecontroller/processor 225 can move data into or out of the memory 230 asrequired by an executing process.

The controller/processor 225 is also coupled to the backhaul or networkinterface 235. The backhaul or network interface 235 allows the gNB 102to communicate with other devices or systems over a backhaul connectionor over a network. The interface 235 could support communications overany suitable wired or wireless connection(s). For example, when the gNB102 is implemented as part of a cellular communication system (such asone supporting 5G/NR, LTE, or LTE-A), the interface 235 could allow thegNB 102 to communicate with other gNBs over a wired or wireless backhaulconnection. When the gNB 102 is implemented as an access point, theinterface 235 could allow the gNB 102 to communicate over a wired orwireless local area network or over a wired or wireless connection to alarger network (such as the Internet). The interface 235 includes anysuitable structure supporting communications over a wired or wirelessconnection, such as an Ethernet or RF transceiver.

The memory 230 is coupled to the controller/processor 225. Part of thememory 230 could include a RAM, and another part of the memory 230 couldinclude a Flash memory or other ROM.

Although FIG. 2 illustrates one example of gNB 102, various changes maybe made to FIG. 2. For example, the gNB 102 could include any number ofeach component shown in FIG. 2. As a particular example, an access pointcould include a number of interfaces 235, and the controller/processor225 could support routing functions to route data between differentnetwork addresses. As another particular example, while shown asincluding a single instance of TX processing circuitry 215 and a singleinstance of RX processing circuitry 220, the gNB 102 could includemultiple instances of each (such as one per RF transceiver). Also,various components in FIG. 2 could be combined, further subdivided, oromitted and additional components could be added according to particularneeds.

FIG. 3 illustrates an example UE 116 according to embodiments of thepresent disclosure. The embodiment of the UE 116 illustrated in FIG. 3is for illustration only, and the UEs 111-115 of FIG. 1 could have thesame or similar configuration. However, UEs come in a wide variety ofconfigurations, and FIG. 3 does not limit the scope of this disclosureto any particular implementation of a UE.

As shown in FIG. 3, the UE 116 includes an antenna 305, a radiofrequency (RF) transceiver 310, TX processing circuitry 315, amicrophone 320, and receive (RX) processing circuitry 325. The UE 116also includes a speaker 330, a processor 340, an input/output (I/O)interface (IF) 345, a touchscreen 350, a display 355, and a memory 360.The memory 360 includes an operating system (OS) 361 and one or moreapplications 362.

The RF transceiver 310 receives, from the antenna 305, an incoming RFsignal transmitted by a gNB of the network 100. The RF transceiver 310down-converts the incoming RF signal to generate an intermediatefrequency (IF) or baseband signal. The IF or baseband signal is sent tothe RX processing circuitry 325, which generates a processed basebandsignal by filtering, decoding, and/or digitizing the baseband or IFsignal. The RX processing circuitry 325 transmits the processed basebandsignal to the speaker 330 (such as for voice data) or to the processor340 for further processing (such as for web browsing data).

The TX processing circuitry 315 receives analog or digital voice datafrom the microphone 320 or other outgoing baseband data (such as webdata, e-mail, or interactive video game data) from the processor 340.The TX processing circuitry 315 encodes, multiplexes, and/or digitizesthe outgoing baseband data to generate a processed baseband or IFsignal. The RF transceiver 310 receives the outgoing processed basebandor IF signal from the TX processing circuitry 315 and up-converts thebaseband or IF signal to an RF signal that is transmitted via theantenna 305.

The processor 340 can include one or more processors or other processingdevices and execute the OS 361 stored in the memory 360 in order tocontrol the overall operation of the UE 116. For example, the processor340 could control the reception of forward channel signals and thetransmission of reverse channel signals by the RF transceiver 310, theRX processing circuitry 325, and the TX processing circuitry 315 inaccordance with well-known principles. In some embodiments, theprocessor 340 includes at least one microprocessor or microcontroller.

The processor 340 is also capable of executing other processes andprograms resident in the memory 360, such as processes for a multipleantenna channel tracking operation. The processor 340 can move data intoor out of the memory 360 as required by an executing process. In someembodiments, the processor 340 is configured to execute the applications362 based on the OS 361 or in response to signals received from gNBs oran operator. The processor 340 is also coupled to the I/O interface 345,which provides the UE 116 with the ability to connect to other devices,such as laptop computers and handheld computers. The I/O interface 345is the communication path between these accessories and the processor340.

The processor 340 is also coupled to the touchscreen 350 and the display355. The operator of the UE 116 can use the touchscreen 350 to enterdata into the UE 116. The display 355 may be a liquid crystal display,light emitting diode display, or other display capable of rendering textand/or at least limited graphics, such as from web sites.

The memory 360 is coupled to the processor 340. Part of the memory 360could include a random access memory (RAM), and another part of thememory 360 could include a Flash memory or other read-only memory (ROM).

Although FIG. 3 illustrates one example of UE 116, various changes maybe made to FIG. 3. For example, various components in FIG. 3 could becombined, further subdivided, or omitted and additional components couldbe added according to particular needs. As a particular example, theprocessor 340 could be divided into multiple processors, such as one ormore central processing units (CPUs) and one or more graphics processingunits (GPUs). Also, while FIG. 3 illustrates the UE 116 configured as amobile telephone or smartphone, UEs could be configured to operate asother types of mobile or stationary devices.

To meet the demand for wireless data traffic having increased sincedeployment of 4G communication systems and to enable various verticalapplications, 5G/NR communication systems have been developed and arecurrently being deployed. The 5G/NR communication system is consideredto be implemented in higher frequency (mmWave) bands, e.g., 28 GHz or 60GHz bands, so as to accomplish higher data rates or in lower frequencybands, such as 6 GHz, to enable robust coverage and mobility support. Todecrease propagation loss of the radio waves and increase thetransmission distance, the beamforming, massive multiple-inputmultiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna,an analog beam forming, large scale antenna techniques are discussed in5G/NR communication systems.

In addition, in 5G/NR communication systems, development for systemnetwork improvement is under way based on advanced small cells, cloudradio access networks (RANs), ultra-dense networks, device-to-device(D2D) communication, wireless backhaul, moving network, cooperativecommunication, coordinated multi-points (CoMP), reception-endinterference cancellation and the like.

The discussion of 5G systems and frequency bands associated therewith isfor reference as certain embodiments of the present disclosure may beimplemented in 5G systems. However, the present disclosure is notlimited to 5G systems or the frequency bands associated therewith, andembodiments of the present disclosure may be utilized in connection withany frequency band. For example, aspects of the present disclosure mayalso be applied to deployment of 5G communication systems, 6G or evenlater releases which may use terahertz (THz) bands.

A communication system includes a downlink (DL) that refers totransmissions from a base station or one or more transmission points toUEs and an uplink (UL) that refers to transmissions from UEs to a basestation or to one or more reception points.

A time unit for DL signaling or for UL signaling on a cell is referredto as a slot and can include one or more symbols. A symbol can alsoserve as an additional time unit. A frequency (or bandwidth (BW)) unitis referred to as a resource block (RB). One RB includes a number ofsub-carriers (SCs). For example, a slot can have duration of 0.5milliseconds or 1 millisecond, include 14 symbols and an RB can include12 SCs with inter-SC spacing of 30 KHz or 15 KHz, and so on.

DL signals include data signals conveying information content, controlsignals conveying DL control information (DCI), and reference signals(RS) that are also known as pilot signals. A gNB transmits datainformation or DCI through respective physical DL shared channels(PDSCHs) or physical DL control channels (PDCCHs). A PDSCH or a PDCCHcan be transmitted over a variable number of slot symbols including oneslot symbol. For brevity, a DCI format scheduling a PDSCH reception by aUE is referred to as a DL DCI format and a DCI format scheduling aphysical uplink shared channel (PUSCH) transmission from a UE isreferred to as an UL DCI format.

A gNB transmits one or more of multiple types of RS including channelstate information RS (CSI-RS) and demodulation RS (DMRS). A CSI-RS isprimarily intended for UEs to perform measurements and provide CSI to agNB. For channel measurement, non-zero power CSI-RS (NZP CSI-RS)resources are used. For interference measurement reports (IMRs), CSIinterference measurement (CSI-IM) resources associated with a zero powerCSI-RS (ZP CSI-RS) configuration are used. A CSI process includes NZPCSI-RS and CSI-IM resources.

A UE can determine CSI-RS transmission parameters through DL controlsignaling or higher layer signaling, such as radio resource control(RRC) signaling, from a gNB. Transmission instances of a CSI-RS can beindicated by DL control signaling or be configured by higher layersignaling. A DM-RS is transmitted only in the BW of a respective PDCCHor PDSCH and a UE can use the DMRS to demodulate data or controlinformation.

FIG. 4 and FIG. 5 illustrate example wireless transmit and receive pathsaccording to this disclosure. In the following description, a transmitpath 400 may be described as being implemented in a gNB (such as the gNB102), while a receive path 500 may be described as being implemented ina UE (such as a UE 116). However, it may be understood that the receivepath 500 can be implemented in a gNB and that the transmit path 400 canbe implemented in a UE. In some embodiments, the receive path 500 isconfigured to support the beam indication channel in a multi-beam systemas described in embodiments of the present disclosure.

The transmit path 400 as illustrated in FIG. 4 includes a channel codingand modulation block 405, a serial-to-parallel (S-to-P) block 410, asize N inverse fast Fourier transform (IFFT) block 415, aparallel-to-serial (P-to-S) block 420, an add cyclic prefix block 425,and an up-converter (UC) 430. The receive path 500 as illustrated inFIG. 5 includes a down-converter (DC) 555, a remove cyclic prefix block560, a serial-to-parallel (S-to-P) block 565, a size N fast Fouriertransform (FFT) block 570, a parallel-to-serial (P-to-S) block 575, anda channel decoding and demodulation block 580.

As illustrated in FIG. 4, the channel coding and modulation block 405receives a set of information bits, applies coding (such as alow-density parity check (LDPC) coding), and modulates the input bits(such as with quadrature phase shift keying (QPSK) or quadratureamplitude modulation (QAM)) to generate a sequence of frequency-domainmodulation symbols.

The serial-to-parallel block 410 converts (such as de-multiplexes) theserial modulated symbols to parallel data in order to generate Nparallel symbol streams, where N is the IFFT/FFT size used in the gNB102 and the UE 116. The size N IFFT block 415 performs an IFFT operationon the N parallel symbol streams to generate time-domain output signals.The parallel-to-serial block 420 converts (such as multiplexes) theparallel time-domain output symbols from the size N IFFT block 415 inorder to generate a serial time-domain signal. The add cyclic prefixblock 425 inserts a cyclic prefix to the time-domain signal. Theup-converter 430 modulates (such as up-converts) the output of the addcyclic prefix block 425 to an RF frequency for transmission via awireless channel. The signal may also be filtered at baseband beforeconversion to the RF frequency.

A transmitted RF signal from the gNB 102 arrives at the UE 116 afterpassing through the wireless channel, and reverse operations to those atthe gNB 102 are performed at the UE 116.

As illustrated in FIG. 5, the down-converter 555 down-converts thereceived signal to a baseband frequency, and the remove cyclic prefixblock 560 removes the cyclic prefix to generate a serial time-domainbaseband signal. The serial-to-parallel block 565 converts thetime-domain baseband signal to parallel time domain signals. The size NFFT block 570 performs an FFT algorithm to generate N parallelfrequency-domain signals. The parallel-to-serial block 575 converts theparallel frequency-domain signals to a sequence of modulated datasymbols. The channel decoding and demodulation block 580 demodulates anddecodes the modulated symbols to recover the original input data stream.

Each of the gNB s 101-103 may implement a transmit path 400 asillustrated in FIG. 4 that is analogous to transmitting in the downlinkto UEs 111-116 and may implement a receive path 500 as illustrated inFIG. 5 that is analogous to receiving in the uplink from UEs 111-116.Similarly, each of UEs 111-116 may implement the transmit path 400 fortransmitting in the uplink to the gNBs 101-103 and may implement thereceive path 500 for receiving in the downlink from the gNBs 101-103.

Each of the components in FIG. 4 and FIG. 5 can be implemented usingonly hardware or using a combination of hardware and software/firmware.As a particular example, at least some of the components in FIG. 4 andFIG. 5 may be implemented in software, while other components may beimplemented by configurable hardware or a mixture of software andconfigurable hardware. For instance, the FFT block 570 and the IFFTblock 415 may be implemented as configurable software algorithms, wherethe value of size N may be modified according to the implementation.

Furthermore, although described as using FFT and IFFT, this is by way ofillustration only and may not be construed to limit the scope of thisdisclosure. Other types of transforms, such as discrete Fouriertransform (DFT) and inverse discrete Fourier transform (IDFT) functions,can be used. It may be appreciated that the value of the variable N maybe any integer number (such as 1, 2, 3, 4, or the like) for DFT and IDFTfunctions, while the value of the variable N may be any integer numberthat is a power of two (such as 1, 2, 4, 8, 16, or the like) for FFT andIFFT functions.

Although FIG. 4 and FIG. 5 illustrate examples of wireless transmit andreceive paths, various changes may be made to FIG. 4 and FIG. 5. Forexample, various components in FIG. 4 and FIG. 5 can be combined,further subdivided, or omitted and additional components can be addedaccording to particular needs. Also, FIG. 4 and FIG. 5 are meant toillustrate examples of the types of transmit and receive paths that canbe used in a wireless network. Any other suitable architectures can beused to support wireless communications in a wireless network.

FIG. 6 illustrates an example antenna structure 600 according toembodiments of the present disclosure. An embodiment of the antennastructure 600 shown in FIG. 6 is for illustration only.

For mmWave bands, although the number of antenna elements can be largerfor a given form factor, the number of CSI-RS ports—which can correspondto the number of digitally precoded ports—tends to be limited due tohardware constraints (such as the feasibility to install a large numberof ADCs/DACs at mmWave frequencies) as illustrated by beamformingarchitecture 600 in FIG. 6. In this case, one CSI-RS port is mapped ontoa large number of antenna elements which can be controlled by a bank ofanalog phase shifters 601. One CSI-RS port can then correspond to onesub-array which produces a narrow analog beam through analog beamforming605. This analog beam can be configured to sweep across a wider range ofangles 620 by varying the phase shifter bank across symbols or subframesor slots (wherein a subframe or a slot comprises a collection of symbolsand/or can comprise a transmission time interval). The number ofsub-arrays (equal to the number of RF chains) is the same as the numberof CSI-RS ports N_(CSI-PORT). A digital beamforming unit 610 performs alinear combination across N_(CSI-PORT) analog beams to further increaseprecoding gain. While analog beams are wideband (hence notfrequency-selective), digital precoding can be varied across frequencysub-bands or resource blocks.

FIG. 7 illustrates a flowchart of a method 700 for a channel predictionoperation according to embodiments of the present disclosure. Forexample, the method 700 may be implemented by a base station such as101-103 as illustrated in FIG. 1. An embodiment of the method 700 shownin FIG. 7 is for illustration only. One or more of the componentsillustrated in FIG. 7 can be implemented in specialized circuitryconfigured to perform the noted functions or one or more of thecomponents can be implemented by one or more processors executinginstructions to perform the noted functions.

As illustrated in FIG. 7, uplink timing and frequency offsets areunavoidable effect that are caused by UEs. A random timing offset in thepresent disclosure refers to the sample-wise UL timing adjustmentperformed by a UE at random time instances depending on UE's ownassessment of the time drift to eNB/gNB.

Each UE tries to correct a carrier frequency offset (CFO) based ondownlink signals from eNB and leaves an unpredictable amount of aresidual CFO. The impact of the random residual CFO is to induce arandom phase rotation on SRS observed by eNB/gNB, and such phaserotation is common to all eNB/gNB antennas and all frequency samples inthe same SRS symbol.

In a channel prediction problem, a subspace based method can be applied.This type of method tracks the dominant (subspace) directions and timevarying coefficients of channel matrix. The (subspace) direction isrelatively slow-varying in the time domain, while the coefficients ofeach (subspace) direction is fast varying.

When the directions and the coefficients are tracked well, it ispossible to predict the future channel coefficients, hence alleviate thechannel aging effect.

However, the random CFO and timing offset introduces unpredictablefeatures for the coefficients in the time domain. The impact of CFO maybe removed to perform meaningful tracking and prediction. The removal ofCFO impact can be applied to either the subspace tracking/predictionstage or the coefficient tracking/prediction stage.

As illustrated in FIG. 7, at step 702, a base station such as 101-103 asillustrated in FIG. 1 receives SRS at time to. At step 704, the basestation updates an SRS buffer. Subsequently, at step 706, the basestation updates channel prediction parameters. Finally, the base stationat step 708 uses the channel prediction model to derive the futurechannel for time t.

FIG. 8A illustrates an example tracking and prediction operation 800according to embodiments of the present disclosure. For example, thetracking and prediction operation 800 may be implemented by a basestation such as 101-103 as illustrated in FIG. 1. An embodiment of thetracking and prediction operation 800 shown in FIG. 8A is forillustration only. One or more of the components illustrated in FIG. 8Acan be implemented in specialized circuitry configured to perform thenoted functions or one or more of the components can be implemented byone or more processors executing instructions to perform the notedfunctions.

Denote the channel matrix of a certain RB m, at time instance t, asH_(m,t), of dimension N_(R)×N_(T) composed of channel coefficients fromN_(T) transmission antennas, and N_(R) reception antennas. Denote thesrs transmitted from an arbitrary transmission antenna as h_(m,t,n), anN_(R)×1 vector. Below examples focus on channels from one transmissionantenna.

Assuming the channel is composed of P dominant subspace directions, itcan be approximated as: h_(m,t,n)≈h _(m,t,n)=Σ_(p=1 . . . P)α_(p,m,t)w_(p,m,t).

Using a sub-space tracking method, based on past observations fromh_(m,t−T,n), h_(m,t−(2T),n) . . . h_(m,t−kT,n), the correspondingα_(p,m,t−T) , α_(p,m,t−2T), . . . α_(p,m,t−kT) and w_(p,m,t−T),w_(p,m,t−2T), . . . w_(p,m,t−kT) can be estimated.

Assuming the dominant directions w_(p,m,t) change slowly over time, suchthat ŵ_(p,m,t+Δt)≈w_(p,m,t). The coefficient α_(p,m,t) is relativelyfast varying, and one can apply filter {circumflex over(α)}_(p,m,t+Δt)=Σβ(−x)α_(p,m,t−x) to predict future coefficients.

The predicted channel at time t+Δt is constructed as:ĥ_(m,t+Δt,n)=Σ_(p=1 . . . P){circumflex over(α)}_(p,m,t+Δt)ŵ_(p,m,t+Δt).

The computation of requires computation of auto-correlation function(ACF) of α, i.e., c(−x)=E_(i)[α_(p,m,i)·α*_(p,m,i−x)].

However, due to the timing offset (TO) and frequency offset (FO)introduced by the UE clock, a random phase is introduced at every αestimate, i.e., {tilde over (α)}_(p,m,t)=α_(p,m,t)·e^(jϕ) ^(t) , and thecomputed ACF is distorted as: {tilde over (c)}(−x)=E_(i)[α_(p,m,i)e^(jϕ)^(t) ·α*_(p,m,i−x)e^(−jϕ) ^(t−x) ]=E_(i)[α_(p,m,i)·α*_(p,m,i−2)·e^(j(ϕ)^(t) ^(−ϕ) ^(t−s) ^()].)

As a result, the prediction accuracy cannot be guaranteed. However, notethat the random phase does not distort the Eigen/subspace directions.For precoding purpose, channel construction with a phase offset acrossall antennas is acceptable. Therefore, the present disclosure providesto remove the impact of the ToFo by normalizing the phase utilizingantenna differentiation.

As illustrated in FIG. 8A, the noise and To/Fo 802 and the H(t) 804 aresummed and generated into noisy H SRS 806. The noisy H SRS 806 and theprevious subspace basis are entered together. At step 810, the basestation update the subspace basis based on the noisy H SRS 806 and theprevious subspace basis. At step 812, the base station computes subspacecoefficients. At step 814, the base station collects the coefficientbuffer based on the computed subspace coefficients at step 812. At step816, the base station predicts [a1(t+1), a2(t+1) . . . ]. At step 818,the base station predicts H(t+1) with the updated subspace basis at step810.

FIG. 8B illustrates an example antenna array 850 for a tracking andprediction operation according to embodiments of the present disclosure.An embodiment of the antenna array 850 shown in FIG. 8B is forillustration only.

As illustrated in FIG. 8B, an eNB include antenna arrays transmittingthe beam to a UE that is moving in a cell.

In one embodiment, in every TTI, before the processing, the channelcoefficient are normalized by the phase of the coefficient of a fixedreference. The normalization can be performed for either the phase onlyor both the phase and the amplitude. Denote the chosen reference ash_(r), one method is to normalize the channel coefficients as: h^(proc)_(m,t,n)=h_(m,t,n)·e^(−jθ), where θ=∠h_(r).

Another method is to normalize the channel coefficients as:

${h_{m,t,n}^{proc} = {{h_{m,t,n} \cdot \frac{1}{a}}e^{{- j}\theta}}},$

where αe^(jθ)=h_(r).

FIG. 9 illustrates an example ToFo impact removal operation 900 beforeentire processing according to embodiments of the present disclosure.For example, the ToFo impact removal operation 900 may be implemented bya base station such as 101-103 as illustrated in FIG. 1. An embodimentof the ToFo impact removal operation 900 shown in FIG. 9 is forillustration only. One or more of the components illustrated in FIG. 9can be implemented in specialized circuitry configured to perform thenoted functions or one or more of the components can be implemented byone or more processors executing instructions to perform the notedfunctions.

As illustrated in FIG. 9, the noise and To/Fo 902 and the H(t) 904 aresummed and generated into the noisy H SRS H(t) 906. At step 908, thebase station performs the antenna differentiation FO removal. The outputof the antenna differentiation FO removal is used to update the subspacebasis at step 910 and 912. At step 914, the base station computessubspaces coefficients [α1(t), a2(t) . . . ]. At step 916, the basestation collects coefficients buffer. At step 918, the base stationpredicts [a1]t+1), a2(t+1) . . . ]. At step 920, the base stationpredicts H (t+1).

In another embodiment, the ToFo impact removal is performed after thesubspace projection before the subspace coefficients tracking andprediction. The subspace direction coefficients can be normalized withrespect to a certain reference. The normalization can be performed foreither the phase only or both the phase and the amplitude. Denote thereference as h_(r), one method is to normalize the coefficients as: [α₁,α₂, . . . α_(P)]^(proc)=[α₁, α₂, . . . α_(P)]e^(−jθ), where θ=∠h_(r).

In another embodiment, the channel coefficients is normalized as:

${\left\lbrack {\alpha_{1},\alpha_{2},\ldots,\alpha_{P}} \right\rbrack^{proc} = {{\left\lbrack {\alpha_{1},\alpha_{2},\ldots,\alpha_{P}} \right\rbrack \cdot \frac{1}{a}}e^{{- j}\theta}}},$

where αe^(jθ)=h_(r).

FIG. 10 illustrates an example ToFo impact removal operation 1000 afterthe subspace tracking operation according to embodiments of the presentdisclosure. For example, the ToFo impact removal operation 1000 may beimplemented by a base station such as 101-103 as illustrated in FIG. 1.An embodiment of the ToFo impact removal operation 1000 shown in FIG. 10is for illustration only. One or more of the components illustrated inFIG. 10 can be implemented in specialized circuitry configured toperform the noted functions or one or more of the components can beimplemented by one or more processors executing instructions to performthe noted functions.

As illustrated in FIG. 10, the noise and To/Fo 1002 and the H(t) 1004are summed and generated into the noisy H SRS H(t) 1006. At step 1008,the base station updates the subspace basis with the previous subspacebasis 1010. At step 1012, the base station computes subspacescoefficients [a1(t), a2(t) . . . ]. At step 1014, the base stationperforms the subspace coefficients differentiation. At step 1016, thebase station collects coefficients buffer. At step 1018, the basestation predicts [a1]t+1), a2(t+1) . . . ]. At step 1020, the basestation predicts H (t+1).

When selecting the normalization reference h_(r), a few options can beconsidered.

In one embodiment, the reference is selected as an antenna coefficient.The reference antenna can be chosen arbitrarily (but fixed over time) orchosen as the antenna that receives strongest power over an observationwindow.

In another embodiment, the reference antenna is chosen based on antennalocation in the panel. For example, the antennas in the middle or theone that inherently experiences the least radio frequency circuitimpairments.

In another embodiment, the reference is selected as the coefficient of afixed Eigen/subspace direction. The Eigen direction can be chosenarbitrarily or chosen as the Eigen direction that has the strongestpower over an observation window.

In another embodiment, a history of the signal received by theaforementioned reference may be used to further produce a betterreference by means of filtering or denoising.

FIG. 11 illustrates an example antenna differentiation followed bychannel tracking operation 1100 according to embodiments of the presentdisclosure. For example, the antenna differentiation followed by channeltracking operation 1100 may be implemented by a base station such as101-103 as illustrated in FIG. 1. An embodiment of the antennadifferentiation followed by channel tracking operation 1100 shown inFIG. 11 is for illustration only. One or more of the componentsillustrated in FIG. 11 can be implemented in specialized circuitryconfigured to perform the noted functions or one or more of thecomponents can be implemented by one or more processors executinginstructions to perform the noted functions.

As illustrated in FIG. 11, a base station performs the predictioncontrol at step 1104 based on the SRS buffer 1102 and the updated pathparameters 1118. At step 1106, the base station performs the antennadifferentiation. The output of the antenna differentiation is used forcanonical mode search 1108 and the gamma tracking 1110. The output ofthe canonical mode search 1108 is used for the grid search 1113. Theoutput of the gamma tracking 1110 is used for the delay EKF 1114 and theDoppler EKF 1116. The output of the grid search 1112 and the output ofthe Doppler EKF are used for updating the path parameters 1118. The basestation performs the channel reconstruction based on the updated pathparameter 1118. The output of the channel reconstruction 1120 and theoutput of the adaptive SH residual(A-SHRes) 1124 are used to be combinedinto DSP/precoding FPGA 1122.

Without the removal, the coefficients are very difficult to track, andthe prediction is less inaccurate.

It may be observed that the channel coefficients on all the eNB antennaelements may not follow the same process. For instance, the eNB antennasare divided into two groups according to the polarization, the twogroups display different power, and different estimated delay.

In one example, it is beneficial to divide the antennas into group(s)and perform the tracking/prediction on each group individually.

The aforementioned normalization can be performed to all group(s)jointly or for each group individually.

The reference can be chosen common for all group(s), or separately foreach group.

FIG. 12 illustrates a flowchart of a method 1200 for a multiple antennachannel tracking procedure according to embodiments of the presentdisclosure. For example, the method 1200 may be implemented by a basestation such as 101-103 as illustrated in FIG. 1. An embodiment of themethod 1200 shown in FIG. 12 is for illustration only. One or more ofthe components illustrated in FIG. 12 can be implemented in specializedcircuitry configured to perform the noted functions or one or more ofthe components can be implemented by one or more processors executinginstructions to perform the noted functions.

As illustrated in FIG. 12, the method 1200 begins at step 1202. In step1202, a BS identifies antenna groups.

Subsequently, in step 1204, the BS identifies channel coefficients foreach of the antenna groups to perform a channel tracking and predictionoperation.

Next, in step 1206, the BS receives, from a user equipment (UE), anuplink signal to perform the channel tracking and prediction operation.

Finally, in step 1208, the BS performs, based at least in part on thereceived uplink signal, a channel coefficient tracking operation for thechannel coefficients of the antenna groups, respectively, the channelcoefficient tracking operation including a channel subspace parametertracking operation and a subspace coefficient tracking operation.

In one embodiment, the BS identifies the antenna groups based onpolarization directions of antennas, respectively, in the antennagroups, respectively or identifies the antenna groups based on geometrydistances between the antennas, respectively, in antenna groups,respectively.

In one embodiment, the BS normalizes, based on a reference antenna, thechannel coefficients for the antenna groups, respectively, based on atleast one of a phase or an amplitude for an antenna differentiationoperation and performs the channel tracking and prediction operationbased on the normalized channel coefficients for the antenna groups,respectively.

In one embodiment, the BS normalizes the channel coefficients for theantenna groups, respectively, each of the antenna groups being jointlyor individually normalized.

In one embodiment, the BS identifies subspace coefficients for theantenna groups, respectively, normalizes, based on a reference antennaor a subspace coefficient, the subspace coefficients for the antennagroups, respectively, based on at least one of a phase or an amplitudefor a subspace coefficients differentiation operation, and performs thechannel tracking and prediction operation based on the normalizedsubspace coefficients for the antenna groups, respectively.

In one embodiment, the BS normalizes the subspace coefficients for theantenna groups, respectively, each of the antenna groups being jointlyor individually normalized.

In one embodiment, the BS randomly selects an antenna in the antennagroups and determining the selected antenna as a reference antenna forthe channel subspace parameter tracking operation and a subspacecoefficient tracking operation, or randomly selects a subspacecoefficient and determining the selected subspace coefficient as areference coefficient for the channel subspace parameter trackingoperation and a subspace coefficient tracking operation.

In one embodiment, the BS identifies an observation window for measuringpower of the antennas, selects, based on the observation window, anantenna with highest power among the antennas, and determines theselected antenna as a reference antenna for the channel subspaceparameter tracking operation and a subspace coefficient trackingoperation.

In one embodiment, the BS identifies an observation window for measuringpower of the antennas, selects, based on the observation window, asubspace coefficient, and determines the selected subspace coefficientas a reference coefficient for the channel subspace parameter trackingoperation and a subspace coefficient tracking operation.

For illustrative purposes the steps of this algorithm are describedserially, however, some of these steps may be performed in parallel toeach other. The above operation diagrams illustrate example methods thatcan be implemented in accordance with the principles of the presentdisclosure and various changes could be made to the methods illustratedin the flowcharts herein. For example, while shown as a series of steps,various steps in each figure could overlap, occur in parallel, occur ina different order, or occur multiple times. In another example, stepsmay be omitted or replaced by other steps.

Although the present disclosure has been described with exemplaryembodiments, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosure encompasssuch changes and modifications as fall within the scope of the appendedclaims. None of the description in this application should be read asimplying that any particular element, step, or function is an essentialelement that must be included in the claims scope. The scope of patentedsubject matter is defined by the claims.

What is claimed is:
 1. A base station (BS) comprising: a processorconfigured to: identify antenna groups, and identify channelcoefficients for each of the antenna groups to perform a channeltracking and prediction operation; and a transceiver operably connectedto the processor, the transceiver configured to receive, from a userequipment (UE), an uplink signal to perform the channel tracking andprediction operation, wherein the processor is further configured toperform, based at least in part on the received uplink signal, a channelcoefficient tracking operation for the channel coefficients of theantenna groups, respectively, the channel coefficient tracking operationincluding a channel subspace parameter tracking operation and a subspacecoefficient tracking operation.
 2. The BS of claim 1, wherein theprocessor is further configured to: identify the antenna groups based onpolarization directions of antennas, respectively, in the antennagroups, respectively; or identify the antenna groups based on geometrydistances between the antennas, respectively, in antenna groups,respectively.
 3. The BS of claim 1, wherein the processor is furtherconfigured to: normalize, based on a reference antenna, the channelcoefficients for the antenna groups, respectively, based on at least oneof a phase or an amplitude for an antenna differentiation operation; andperform the channel tracking and prediction operation based on thenormalized channel coefficients for the antenna groups, respectively. 4.The BS of claim 3, wherein the processor is further configured tonormalize the channel coefficients for the antenna groups, respectively,each of the antenna groups being jointly or individually normalized. 5.The BS of claim 1, wherein the processor is further configured to:identify subspace coefficients for the antenna groups, respectively;normalize, based on a reference antenna or a subspace coefficient, thesubspace coefficients for the antenna groups, respectively, based on atleast one of a phase or an amplitude for a subspace coefficientsdifferentiation operation; and perform the channel tracking andprediction operation based on the normalized subspace coefficients forthe antenna groups, respectively.
 6. The BS of claim 5, wherein theprocessor is further configured to normalize the subspace coefficientsfor the antenna groups, respectively, each of the antenna groups beingjointly or individually normalized.
 7. The BS of claim 1, wherein theprocessor is further configured to: randomly select an antenna in theantenna groups and determine the selected antenna as a reference antennafor the channel subspace parameter tracking operation and a subspacecoefficient tracking operation; or randomly select a subspacecoefficient and determine the selected subspace coefficient as areference coefficient for the channel subspace parameter trackingoperation and a subspace coefficient tracking operation.
 8. The BS ofclaim 1, wherein the processor is further configured to: identify anobservation window for measuring power of the antennas; select, based onthe observation window, an antenna with highest power among theantennas; and determine the selected antenna as a reference antenna forthe channel subspace parameter tracking operation and a subspacecoefficient tracking operation.
 9. The BS of claim 1, wherein theprocessor is further configured to: identify an observation window formeasuring power of the antennas; select, based on the observationwindow, a subspace coefficient; and determine the selected subspacecoefficient as a reference coefficient for the channel subspaceparameter tracking operation and a subspace coefficient trackingoperation.
 10. A method of a base station (BS), the method comprising:identifying antenna groups; identifying channel coefficients for each ofthe antenna groups to perform a channel tracking and predictionoperation; receiving, from a user equipment (UE), an uplink signal toperform the channel tracking and prediction operation; and performing,based at least in part on the received uplink signal, a channelcoefficient tracking operation for the channel coefficients of theantenna groups, respectively, the channel coefficient tracking operationincluding a channel subspace parameter tracking operation and a subspace coefficient tracking operation.
 11. The method of claim 10,further comprising: identifying the antenna groups based on polarizationdirections of antennas, respectively, in the antenna groups,respectively; or identifying the antenna groups based on geometrydistances between the antennas, respectively, in antenna groups,respectively.
 12. The method of claim 10, further comprising:normalizing, based on a reference antenna, the channel coefficients forthe antenna groups, respectively, based on at least one of a phase or anamplitude for an antenna differentiation operation; and performing thechannel tracking and prediction operation based on the normalizedchannel coefficients for the antenna groups, respectively.
 13. Themethod of claim 12, further comprising normalizing the channelcoefficients for the antenna groups, respectively, each of the antennagroups being jointly or individually normalized.
 14. The method of claim10, further comprising: identifying subspace coefficients for theantenna groups, respectively; normalizing, based on a reference antennaor a subspace coefficient, the subspace coefficients for the antennagroups, respectively, based on at least one of a phase or an amplitudefor a subspace coefficients differentiation operation; and performingthe channel tracking and prediction operation based on the normalizedsubspace coefficients for the antenna groups, respectively.
 15. Themethod of claim 14, further comprising normalizing the subspacecoefficients for the antenna groups, respectively, each of the antennagroups being jointly or individually normalized.
 16. The method of claim10, further comprising: randomly selecting an antenna in the antennagroups and determining the selected antenna as a reference antenna forthe channel subspace parameter tracking operation and a subspacecoefficient tracking operation; or randomly selecting a subspacecoefficient and determining the selected subspace coefficient as areference coefficient for the channel subspace parameter trackingoperation and a subspace coefficient tracking operation.
 17. The methodof claim 10, further comprising: identifying an observation window formeasuring power of the antennas; selecting, based on the observationwindow, an antenna with highest power among the antennas; anddetermining the selected antenna as a reference antenna for the channelsubspace parameter tracking operation and a subspace coefficienttracking operation.
 18. The method of claim 10, further comprising:identifying an observation window for measuring power of the antennas;selecting, based on the observation window, a subspace coefficient; anddetermining the selected subspace coefficient as a reference coefficientfor the channel subspace parameter tracking operation and a subspacecoefficient tracking operation.
 19. A non-transitory computer-readablemedium comprising program code, that when executed by a processor,causes a base station (BS) to: identify antenna groups; identify channelcoefficients for each of the antenna groups to perform a channeltracking and prediction operation; receive, from a user equipment (UE),an uplink signal to perform the channel tracking and predictionoperation; and perform, based at least in part on the received uplinksignal, a channel coefficient tracking operation for the channelcoefficients of the antenna groups, respectively, the channelcoefficient tracking operation including a channel subspace parametertracking operation and a subspace coefficient tracking operation. 20.The non-transitory computer-readable medium of claim 19, furthercomprising program code, that when executed by a processor, causes theBS to: identify the antenna groups based on polarization directions ofantennas, respectively, in the antenna groups, respectively; or identifythe antenna groups based on geometry distances between the antennas,respectively, in antenna groups, respectively.